1,721,127 research outputs found
SOILPAR 2.00 : Software to estimate soil hydrological parameters and functions
No full textSOILPAR 2 is a program for estimating soil parameters. It allows: (1) storing soil data in a georeferenced database, (2) computing estimates of soil hydrological parameters using 15 procedures, (3) comparing the estimates against measured data using both statistical indices and graphics, and (4) creating maps using the ESRI format. An interface to/from Excel and CropSyst is provided. Eleven methods estimate one or more of the following characteristics: soil water content at predefined soil matrix tension, saturated hydraulic conductivity, and bulk density. Three methods estimate the parameters of well-known soil water retention functions (Brooks-Corey, Hutson-Cass, van Genuchten), and one estimates both saturated soil hydraulic conductivity and the soil water retention curve parameters (Campbell). The software runs under Windows 98/NT/2000/XP and is freely downloadable via internet
A set of software components for the simulation of plant airborne diseases
No full textModels to evaluate the impact of plant diseases on crop production under current and future climatic conditions are increasingly requested by different stakeholders. This paper presents four software components - InoculumPressure, DiseaseProgress, ImpactsOnPlants, AgromanagementDisease - which implement models to simulate the dynamics of generic polycyclic fungal epidemics and interactions with crop physiological processes. The software architecture adopted allows extending the components with alternate approaches to reproduce specific pathosystems or compare predictive capabilities. As proofs of concept, (i) the components are coupled with two crop simulators to reproduce wheat brown rust and rice blast epidemics and their impacts on leaf area and yield formation; (ii) spatially distributed sensitivity analyses are performed for rice in China and wheat in Europe to investigate model behaviour; (iii) a preliminary evaluation against observations of rice blast severity is performed in Northern Italy. The components are explicitly targeted to the modelling of crop-pathogen interactions to perform scenario analysis
Biophysical models for cropping system simulation
No full textThe definition of mathematical models to estimate plants growth as a function of environmental variables has started many decades ago, for instance expressing the biomass growth of a plant as a function of the solar radiation intercepted (Warren Wilson 1967). Since then, crop models have evolved including sub-models to estimate plant development, and several other processes relevant to the simulation of the interaction plant-soil as affected by weather and agricultural management. Two main goals can be identified as drivers in plant model development: (1) studying the genotype × environment interaction, as a support tool to variety selection within a given species, or (2) studying production enterprises, hence comparing, from a biophysical point of view, yield, resource use, and externalities of agricultural production systems. Whether most of the models of the former group are specialized to a single crop, the latter includes multi-crop models to simulate crop sequences as in most production systems
PTF: an Extensible Component for Sharing and Using Knowledge on Pedo-Transfer functions
No full textSoil data availability for modelling purposes is often insufficient for the application of physical or semi-empirical models simulating soil hydrology. Standard soil surveys frequently do not include hydrological characteristics of the soil, such as either parameters of water retention and conductivity functions or, simpler than the former, estimates of soil water content at field capacity and wilting point. Even when at least part of such data is available, a quality control is needed to ensure not only that values fit within expected ranges, but also to check for consistency across parameters in a specific soil. The use of pedotransfer functions (PTF) allows estimating "what we need from what we have", that is, it allows estimating soil hydrological parameters from soil data often available. The literature makes available a large number of PTF, and new ones are being proposed. Such PTF range from very simple empirical functions, to complex soil physical models. Users must select a PTF to be used based on both available data and their a-priori knowledge about the soil to be simulated. Still, the choice of the PTF to be used is at times controversial, and users may want to compare the estimate made by several PTF against the same data. Also, users may want to test their own PTF, may be specific for a set of soils and thus perfectly adequate for application in a specific contest, against well known ones. An extensible and easily reusable library encapsulating a collection of PTF can be an important tool to support development and operational use of soil-related models, and to share the increasing knowledge about PTF. The objective of this paper is to illustrate the free available component PTF (PedoTransfer Functions). The component is available for both Windows.NET and JAVA platforms, and it is made available with some proof of concept applications (inclusive of source code) in C#, VB.NET and Java, which show how to extend the component and how to use it. The software component presented in this paper meets the following main requirement: i) easy to reuse; ii) with a clear ontology of the variables used in each PTF, where units, value range, and significance, are unambiguously defined; iii) extensible by third parties independently, allowing for an open system to which scientists can contribute; iv) freely available for non-commercial use
New indices to quantify patterns of residuals produced by model estimates
No full textThe evaluation of patterns in the residuals of model estimates vs. other variables can be useful in both model evaluation and parameter calibration. New indices that allow quantifying such patterns (pattern indices) are presented. Groups of residuals are created by dividing the range of the variable under evaluation into two, three, four, or five subranges. Two types of indices are proposed. The first type (PI-type) is based on the absolute value of the maximum difference between pairwise comparisons among average residuals of each group of residuals. A variant of this index is computed by using variance ratios (PI-F type). The subranges of the variable that determines the grouping of residuals may be of equal length (PI) or variable length (PIv). In the second case, they are generated by an algorithm that optimizes subranges to maximize patterns. The power of the diverse pattern indices at identifying patterns was investigated, and their effectiveness was compared against the runs test. Critical values for pattern indices were generated by Monte Carlo simulations. Monte Carlo probability tables, the results of power analysis, and the results of using pattern indices at two case studies (i.e., daily radiation and soil water content estimates) were presented. The analysis based on pattern indices provided insight in model structure and parameter calibration. Pattern indices also allowed evaluating model performance and discriminating among alternative models. Higher power in identifying patterns was given by range-based pattern indices than by those based on variance ratios
Crop modelling and validation : integration of IRENE_DLL in the WARM environment
No full textThe growing importance of biophysical models in research and application-oriented projects is driving a growing interest in
developing suitable approaches to evaluate model performance. Valuable validation techniques should assess the performance
of complex models under a variety of conditions, and should include a wide range of validation measures. After discussing
validation issues and methods currently used to assess the quality of simulation models, the integration of the software
component for model output evaluation IRENE_DLL within the rice modelling system WARM is illustrated. The
purpose is to demonstrate, via a case study, that great utility in validation can be gained through the implementation and use
of object-oriented software tools targeting at modularity and reusability inside a modelling environment. This facilitates
model validation sessions and extensibility of tools towards new approaches possibly coming out of research. These challenges
can be met by using a wide range of approaches and by expanding horizons in validation whilst tailoring the evaluation
requirements to the specific objectives of the model application. The availability of appropriate software tools allow
actions that are not frequently executed within the context of project-based modelling activities, thus helping the dissemination
of validation experiences and preventing future modelling projects from repetition of validation efforts
A software component to compute agro-meteorological indicators
No full textClimIndices is a software component to compute agro-meteorological indicators on yearly series of daily weather data. The component is released as .NET2 dynamic link libraries (DLL), allowing the development of clients under Windows using .NET languages. The design allows extending the computing capabilities without requiring re-compilation
Evaluating the suitability of a generic fungal infection model for pest risk assessment studies
No full textPest risk assessment studies are aimed at evaluating if weather conditions are suitable for the potential entry and establishment of an organism in a new environment. For fungal plant pathogens, the crucial aspect to be explored is the fulfillment of the infection process, that constitutes the first phase of the development of an epidemic as mainly driven by temperature and leaf wetness duration. This is of particular interest for climate change studies, because the modified pattern of temperature and moisture regimes could completely alter the known distribution and severity of plant disease epidemics. Biophysical process-based models could effectively be used in such studies, because they allow, within their applicability range, estimating organisms responses to climatic drivers in environmental conditions not yet experienced. One of the prerequisite of their adoption in operational contexts is a sensitivity analysis assessment aimed at understanding their ability (i) to differentiate the responses according to different parameterizations and (ii) to be sensitive to the variability of the input data. In this study, a generic potential fungal infection model simulating four pathogens chosen to provide a wide range in temperature and moisture requirements was analyzed. The model was run under diverse climatic conditions. The sensitivity of the model significantly changed according to the pathogen tested, and the relevance of its parameters in explaining model output resulted strongly linked to the environmental conditions tested, indicating its to be used in pest risk assessment studies
- …
